| The low-dopamine state as is seen in Parkinson's disease (PD) is marked by an increase in oscillatory and synchronous activity in the beta band. While causal relationship between this activity and PD motor symptoms is not completely certain, this activity is probably closely related to the pathologies of motor behavior. Understanding the dynamical nature of this synchronization is essential for the understanding of its function as well as for determining potentially efficient therapeutic ways to suppress this synchrony in PD. We simultaneously record spikes and LFP from subthalamic nucleus of PD patients, analyze the phase synchronization between these signals on a fine time scale and use computational models to explore network mechanisms of the observed dynamics. Synchronized dynamics is interrupted by desynchronization events, which are irregular, although not completely random, with a predominance of short desynchronization events. The chances of longer desynchronization events decrease with the duration of these events. The dominance of the short desynchronization events indicates that even though the synchronization in parkinsonian basal ganglia is fragile enough to be frequently destabilized, it has the ability to reestablish itself very quickly, which may be important for the development of the therapeutically relevant methods to suppress this synchrony. The anatomically realistic conductance-based network model of basal ganglia circuits is able to produce similar characteristic fine temporal structure of the synchronous activity. The parameter values correspond to the moderately strong synaptic strengths in the model, which is a realistic case for PD (in a healthy state these synaptic connections would be inhibited by dopamine). While a variety of mechanisms may contribute to the observed specific variability in synchrony on short time scales, the computational results indicate that this variability can be generated intrinsically in basal ganglia circuits without any external inputs due to moderately large strength of synaptic coupling. |
|